Dynamic Grain State Estimation for High-Density TDMR: Progress and Future Directions
Dynamic Grain State Estimation for High-Density TDMR: Progress and Future Directions
复制标题
高密度 TDMR 的动态晶粒状态估计：进展和未来方向
DOI：
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发表时间：
2016
影响因子：
2.1
通讯作者：
K. Sivakumar
中科院分区：
文献类型：
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作者：
Xueliang Sun;B. Belzer;K. Sivakumar
用于二维磁记录 (TDMR) 的动态颗粒状态估计 (DGSE) 算法采用概率消息传递算法，联合估计磁性颗粒配置和编码数据位，以便迭代地协助通道解码。在高密度下（例如，每个编码位 1 到 3 个磁性颗粒），有时，某个位不会写入任何颗粒上，因此将被周围颗粒上的位有效地覆盖（或擦除）。 DGSE 能够检测被覆盖的位，以便为它们的对数似然比分配较小的量值，从而有效地使它们被擦除，很容易由线性通道代码填充。过去在简单的四矩形颗粒模型上使用基于 Bahl-Cocke-Jelinek-Raviv 的检测器的论文表明，DGSE 对于检测器假设的颗粒模型与生成数据的实际模型之间的不匹配具有惊人的弹性。本文提出了一种基于广义置信传播（GBP）算法的新型 DGSE-TDMR 检测器。新探测器采用随机离散核 Voronoi 颗粒模型。仿真结果表明，基于 GBP 的 TDMR Turbo 检测器可以准确地检测到覆盖位，并且在高达每颗粒 0.4966 个用户位的密度下实现了较低的解码误码率。
Dynamic grain state estimation (DGSE) algorithms for 2-D magnetic recording (TDMR) employ probabilistic message-passing algorithms that jointly estimate magnetic grain configurations and coded data bits, in order to iteratively assist channel decoding. At high densities (e.g., between 1 and 3 magnetic grains per coded bit), occasionally, a bit will not be written on any grain, and hence will effectively be overwritten (or erased) by bits on surrounding grains. DGSE enables the detection of overwritten bits so that their log-likelihood ratios are assigned small magnitudes, effectively making them erasures, which are easily filled in by linear channel codes. Past papers employing Bahl-Cocke-Jelinek-Raviv-based detectors on a simple four-rectangular-grain model have shown that the DGSE is surprisingly resilient to mismatch between the detector's assumed grain model and the actual model generating the data. This paper presents a novel DGSE-TDMR detector based on the generalized belief propagation (GBP) algorithm. The new detector employs a random discretized-nuclei Voronoi grain model. Simulation results show that the GBP-based TDMR turbo-detector accurately detects the overwritten bits and that it achieves low decoded bit error rates at densities as high as 0.4966 user bits per grain.